Application of a Chemical Mass Balance Receptor Model to Respirable Particulate Matter in Mexico City

Mexico City frequently experiences high levels of air pollution. This is due mainly to its topography and meteorology that suppress pollutant diffusion and dispersion. The atmospheric mixing is extremely poor, especially during the dry winter months. The levels of certain pollutants, such as particulate matter, are of concern since they have severe effects on public health. Visibility deterioration is one of the most noticeable effects in large cities. Biological effects of particulate matter on man and animals, ranging from mild eye irritation to death, have been reported. The effects depend on the size of the particles, their solubility, and toxicity. The main objective of this paper is to present the results of a chemical mass balance receptor model applied to a well-characterized data set of particulate matter collected in the Mexico City Metropolitan Area (MCMA). Samples of particulate matter were collected using a denuder and a Hi-Vol system for the respi-rable fraction and total suspended particles, respectively. In this paper the analysis of a database consisting of the chemical composition of 33 samples of respirable particulate matter (aerosols with diameter less than 2.5 µm) is presented. The 12-hour samples were acquired during day and night periods in a typical medium-income neighborhood from December 19, 1989 through February 5, 1990.     

Automated Chemical Mass Balance Receptor Modeling

Abstract

A nontrivial portion of heavy-duty vehicle emissions of NO_x and particulate matter (PM) occurs during idling. Regulators and the environmental community are interested in curtailing truck idling emissions, but current emissions models do not characterize them accurately, and little quantitative data exist to evaluate the relative effectiveness of various policies. The objectives of this study were to quantify the effect of accessory loading and engine speed on idling emissions from a properly functioning, modern, heavy-duty diesel truck and to compare these results with data from earlier model year vehicles. It was found that emissions during idling varied greatly as a function of engine model year, engine speed, and accessory load conditions. For the 1999 model year Class 8 truck tested, raising the engine speed from 600 to 1050 rpm and turning on the air conditioning resulted in a 2.5-fold increase in NO_x emissions in grams per hour, a 2-fold increase in CO₂ emissions, and a 5-fold increase in CO emissions while idling. On a grams per gallon fuel basis, NO_x emissions while idling were approximately twice as high as those at 55 mph. The CO₂ emissions at the two conditions were closer. The NO_x emissions from the 1999 truck while idling with air conditioning running were slightly more than those of two 1990 model year trucks under equivalent conditions, and the hydrocarbon (HC) and CO emissions were significantly lower. It was found that the NO_x emissions used in the California Air Resources Board’s (CARB) EMFAC2000 and the U.S. Environmental Protection Agency’s (EPA) MOBILE5b emissions inventory models were lower than those measured in all of the idling conditions tested on the 1999 truck.     

Diagnostics for Determining Influential Species in the Chemical Mass Balance Receptor Model

ABSTRACT

The chemical mass balance (CMB) model can be applied to estimate the amount of airborne particulate matter (PM) coming from various sources given the ambient chemical composition of the particles measured at the receptor and the chemical composition of the source emissions. Of considerable practical importance is the identification of those chemical species that have a large effect on either the source contributions or errors estimated by the CMB model. This paper details a study of a number of influential diagnostics for application of the CMB software. Some of the diagnostics studied are standard regression diagnostics based on single-row deletion diagnostics. A number of new diagnostics were developed specifically for the CMB application, based on the pseudo-inverse of the source composition matrix and called nondeletion diagnostics to distinguish them from the standard deletion diagnostics. Simulated data sets were generated to compare the diagnostics and their response to controlled amounts of random error.

A particular diagnostic called a modified pseudoinverse matrix (MPIN), developed for this study, was found to be the best choice for CMB model application. The MPIN diagnostic contains virtually all the information present in both deletion and nondeletion diagnostics. Since the MPIN diagnostic requires only the source profiles, it can be used to identify influential species in advance without sampling the ambient data and to improve CMB results through possible remedial actions for the influential species. Specific recommendations are given for interpretation and use of the MPIN diagnostic with the CMB model software. Elements with normalized MPIN absolute values of 1 to 0.5 are associated with influential elements. Noninfluential elements have normalized MPIN absolute values of 0.3 or less. Elements with absolute values between 0.3 and 0.5 are ambiguous but should generally be considered noninfluential.     

Applicability of the Mass Concentration Standards for Particulate Matter in Alaskan Areas

The so-called “Six Month Study” of the air toxics problem in the United States was initiated in November 1983 by the U.S. Environmental Protection Agency. The study focused on the magnitude, nature, and distribution of the problem—three major issues that were felt to be most useful to policy makers as they attempted to define the scope and direction of a national program for controlling toxic air pollutants. The following paper is based on a draft staff report on the study released for review in September 1984. The report has not been formally released by the U.S. EPA; a final report is due by late spring of 1985.     

Characterization of Major Chemical Components of Fine Particulate Matter in North Carolina

Abstract

This paper presents measurements of daily sampling of fine particulate matter (PM_2.5) and its major chemical components at three urban and one rural locations in North Carolina during 2002. At both urban and rural sites, the major insoluble component of PM_2.5 is organic matter, and the major soluble components are sulfate (SO₄ ^2?), ammonium (NH₄ ⁺), and nitrate (NO₃ ^?). NH₄ ⁺ is neutralized mainly by SO₄ ^2? rather than by NO₃ ^?, except in winter when SO₄ ^2? concentration is relatively low, whereas NO₃ ^? concentration is high. The equivalent ratio of NH₄ ⁺ to the sum of SO₄ ^2? and NO₃ ^? is <1, suggesting that SO₄ ^2?and NO₃ ^?are not completely neutralized by NH₄ ⁺. At both rural and urban sites, SO₄ ^2?concentration displays a maximum in summer and a minimum in winter, whereas NO₃ ^?displays an opposite seasonal trend. Mass ratio of NO₃ ^? to SO₄ ^2?is consistently <1 at all sites, suggesting that stationary source emissions may play an important role in PM_2.5 formation in those areas. Organic carbon and elemental carbon are well correlated at three urban sites although they are poorly correlated at the agriculture site. Other than the daily samples, hourly samples were measured at one urban site. PM_2.5 mass concen trations display a peak in early morning, and a second peak in late afternoon. Back trajectory analysis shows that air masses with lower PM_2.5 mass content mainly originate from the marine environment or from a continental environment but with a strong subsidence from the upper troposphere. Air masses with high PM_2.5 mass concentrations are largely from continental sources. Our study of fine particulate matter and its chemical composition in North Carolina provides crucial information that may be used to determine the efficacy of the new National Ambient Air Quality Standard (NAAQS) for PM fine. Moreover, the gas-to-particle conversion processes provide improved prediction of long-range transport of pollutants and air quality.     

Particulate Air Pollution in Mexico City: A Collaborative Research Project

ABSTRACT

PM₁₀, PM₂₅, precursor gas, and upper-air meteorological measurements were taken in Mexico City, Mexico, from February 23 to March 22, 1997, to understand concentrations and chemical compositions of the city's particulate matter (PM). Average 24-hr PM₁₀ concentrations over the period of study at the core sites in the city were 75 H g/m³. The 24-hr standard of 150 μ g/m³ was exceeded for seven samples taken during the study period; the maximum 24-hr concentration measured was 542 μ g/m³. Nearly half of the PM₁₀ was composed of fugitive dust from roadways, construction, and bare land. About 50% of the PM₁₀ consisted of PM_2.5, with higher percentages during the morning hours. Organic and black carbon constituted up to half of the PM_2.5. PM concentrations were highest during the early morning and after sunset, when the mixed layers were shallow. Meteorological measurements taken during the field campaign show that on most days air was transported out of the Mexico City basin during the afternoon with little day-to-day carryover.     

Fine Particle Receptor Modeling in the Atmosphere of Mexico City

Abstract

Source apportionment analyses were carried out by means of receptor modeling techniques to determine the contribution of major fine particulate matter (PM_2.5) sources found at six sites in Mexico City. Thirty-six source profiles were determined within Mexico City to establish the fingerprints of particulate matter sources. Additionally, the profiles under the same source category were averaged using cluster analysis and the fingerprints of 10 sources were included. Before application of the chemical mass balance (CMB), several tests were carried out to determine the best combination of source profiles and species used for the fitting. CMB results showed significant spatial variations in source contributions among the six sites that are influenced by local soil types and land use. On average, 24-hr PM_2.5 concentrations were dominated by mobile source emissions (45%), followed by secondary inorganic aerosols (16%) and geological material (17%). Industrial emissions representing oil combustion and incineration contributed less than 5%, and their contribution was higher at the industrial areas of Tlalnepantla (11%) and Xalostoc (8%). Other sources such as cooking, biomass burning, and oil fuel combustion were identified at lower levels. A second receptor model (principal component analysis, [PCA]) was subsequently applied to three of the monitoring sites for comparison purposes. Although differences were obtained between source contributions, results evidence the advantages of the combined use of different receptor modeling techniques for source apportionment, given the complementary nature of their results. Further research is needed in this direction to reach a better agreement between the estimated source contributions to the particulate matter mass.     

A Chemical Mass Balance for Volatile Organics in Chicago

Increasing attention to the presence of atmospheric volatile organic compounds has focused interest on the sources and fate of organics in ambient air. The purpose of this study was to develop a chemical mass balance receptor model (CMB) to determine the contributions of major organic pollution source types to ambient pollution levels. Twenty mid-day ambient air samples were analyzed for the presence of volatile hydrocarbons by gas chromatographlc procedures. Based on these measurements, contributions from vehicles, gasoline vapor emissions, and petroleum refineries to ambient organic concentrations were estimated. For the receptor site studied, vehicles were the dominant source type and accounted for 60.8 percent of the organics evaluated. Contributions from refineries, gasoline vapor, and all other sources were 10.1, 11.1, and 17.9 percent, respectively. Validation of the predictions showed that the model is sensitive to the effect of overall upwind emissions. The CMB model was shown to produce reasonable predictive results for vehicles, gasoline vapor, and refinery contributions to ambient non-methane organic concentrations.     

Chemical composition of fugitive dust emitters in Mexico City

The gravimetric and chemical composition of fugitive dust emitters of Mexico City were analyzed to determine the particulate matter source profiles. Samples of geological material, unpaved and paved roads, agricultural soil, dried lake, asphalt, cement plants, landfill, gravel, and tezontle soil, were collected directly from the ground using a broom and a dustpan. These were dried, sieved and taken through a laboratory resuspension chamber to emulate the natural wind-blown processes of bulk soils and also to provide a uniform deposit on Teflon membrane and quartz fiber filters for further gravimetric and chemical analyses of PM_2.5 and PM₁₀ size fractions. Chemical analyses of the filters included X-ray fluorescence for elemental composition, ion chromatography for water soluble anions, atomic absorption for water soluble metals, automated colorimetric analysis for ammonium and thermal/optical reflectance analysis for carbon species. The data show that most fugitive emitters are composed of 20–30% PM_2.5, which is relatively less than the reported contribution by fossil fuels and biomass (40–60%).     

Assessment of Human Exposure to Ambient Particulate Matter

ABSTRACT

Recent epidemiological studies have consistently shown that the acute mortality effects of high concentrations of ambient particulate matter (PM), documented in historic air pollution episodes, may also be occurring at the low to moderate concentrations of ambient PM found in modern urban areas. In London in December 1952, the unexpected deaths due to PM exposure could be identified and counted as integers by the coroners. In modern times, the PM-related deaths cannot be as readily identified, and they can only be inferred as fractional average daily increases in mortality rates using sophisticated statistical filtering and analyses of the air quality and mortality data. The causality of the relationship between exposure to ambient PM and acute mortality at these lower modern PM concentrations has been questioned because of a perception that there is little significant correlation in time between the ambient PM concentrations and measured personal exposure to PM from all sources (ambient PM plus indoor-generated PM).

This article shows that the critical factor supporting the plausibility of a linear PM mortality relationship is the expected high correlation in time of people's exposure to PM of ambient origin with measured ambient PM concentrations, as used in the epidemiological time series studies. The presence of indoor and personal sources of PM masks this underlying relationship, leading to confusion in the scientific literature about the strong underlying temporal relationship between personal exposure to PM of ambient origin and ambient PM concentration. The authors show that the sources of PM of non-ambient origin operate independently of the ambient PM concentrations, so that the mortality effect of non-ambient PM, if any, must be independent of the effects of the ambient PM exposures.     

Characterization of Particulate Matter in California

ABSTRACT

The size, composition, and concentration of particulate matter (PM) vary with location and time. Several monitoring/sampling programs are operated in California to characterize PM less than 2.5 and 10 µm in aerodynamic diameter (PM_2.5 and PM₁₀). This paper presents a broad summary of the spatial and temporal variations observed in ambient PM_2.5 and PM₁₀ concentrations in California. Many areas that have high PM₁₀ concentrations also have relatively high PM_2.5 concentrations, and data indicate that a significant portion of the PM₁₀ air quality problem is caused by PM_2.5. To develop effective plans for attaining the ambient PM standards, improved understanding of these unique problems is needed. Since 1989, pollution control efforts—whether specifically targeted for particulate matter or indirectly via controls on gaseous emissions—have caused annual average PM_2.5 and PM₁₀ concentrations to decline at most sites in California.     

Day-of-Week Patterns of Particulate Matter and Its Chemical Components at Selected Sites in California

Abstract

This paper analyzes day-of-week variations in concentrations of particulate matter (PM) in California. Because volatile organic compounds (VOCs) and oxides of nitrogen (NO_x) are not only precursors of ozone (O₃) but also of secondary PM, it is useful to know whether the variations by day of week in these precursors are also evident in PM data. Concentrations of PM ≤10 μm (PM₁₀) and ≤2.5[H9262]m in aerodynamic diameter (PM_2.5) were analyzed. PM concentrations exhibit a general weekly pattern, with the maximum occurring late in the workweek and the minimum occurring on weekends (especially Sunday); however, this pattern does not prevail at all sites and areas. PM nitrate (NO₃ ^-) data from Size Selective Inlet (SSI) samplers in the South Coast Air Basin (SoCAB) tend to be somewhat lower on weekends compared with weekdays. During 1988–1991, the weekend average was lower than the weekday average at 8 of 13 locations, with an average decrease of 1%. During 1997–2000, the weekend average was lower than the weekday average at 10 of 13 locations, with an average decrease of 6%. The weekend averages are generally lower than weekday averages for sulfates, organic carbon, and elemental carbon. Because heavy-duty trucks typically represent a major source of elemental carbon, the weekend decrease in heavy-duty truck traffic may also result in a decrease in ambient elemental carbon concentrations.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Source Resolution of Fine Particulate Polycyclic Aromatic Hydrocarbons Using a Receptor Model Modified for Reactivity

This paper provides source contribution estimates from vehicular and meat-cooking emissions to particulate polycyclic aromatic hydrocarbon (PAH) and elemental carbon (EC) concentrations measured at two Los Angeles sites during a field study in 1989. The source concentration matrix for PAH was based on new data for vehicular emissions and literature data for meat-cooking operations. The chemical mass balance (CMB 7.0) receptor model was used, and source profiles were modified to reflect reactive decay of PAH in the atmosphere. The calculations indicate that the Pico Rivera site was dominated by auto emissions, which account for more than 90 percent of all the PAH (except chrysene), carbon monoxide (CO), and 61 percent of the EC concentrations. In contrast, emissions from meat cooking contributed significantly (20 to 75 percent) to the concentrations of four-ring PAH measured at a residential site at Upland. The five-ring and larger PAH were attributed to auto emissions at Upland as well.     

The Application of Chemical Leasing Business Models in Mexico

- DOI: http://dx.doi.org/10.1065/espr2006.02.294 Background, Aim and Scope. To better address the requirements of the changing multilateral order, the United Nations Industrial Development Organization (UNIDO) Cleaner Production Programme, in 2004, developed the new Sustainable Industrial Resource Management (SIRM) approach. This approach is in accordance with the principles decided at the United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro, Brazil in 1992. Unlike the traditional approaches to environmental management, the SIRM concept captures the idea of achieving sustainable industrial development through the implementation of circular material and energy flows in the entire production chain and reduction of the amount of material and energy used with greater efficiency solutions. The SIRM approach seeks to develop new models to encourage a shift from selling products to supplying services, modifying, in this manner, the supplier/user relationship and resulting in a win-win situation for the economy and the environment. Chemical Leasing represents such a new service-oriented business model and is currently being promoted by UNIDO′s Cleaner Production Programme. Main Features. One of the potential approaches to address the problems related to ineffective use and over-consumption of chemicals is the development and implementation of Chemical Leasing business models. These provide concrete solutions to the effective management of chemicals and on the ways negative releases to the environment can be reduced. The Chemical Leasing approach is a strategy that addresses the obligations of the changing international chemicals policy by focusing on a more service-oriented strategy. Mexico is one of the countries that were selected for the implementation of UNIDO's demonstration project to promote Chemical Leasing models in the country. The target sector of this project is the chemical industry, which is expected to shift their traditional business concept towards a more service and value-added approach. This is being achieved through the development of company specific business models that implement the above-indicated Chemical Leasing concept with the support from the Mexican National Cleaner Production Centre (NCPC). Results and Conclusions. The implementation of Chemical Leasing in Mexico has proven to be an efficient instrument in enhancing sustainable chemical management and significantly reducing emissions in Mexico. Several companies from the chemical industrial sector implement or agreed to implement chemical leasing business models. Based on the positive findings of the project, several Mexican companies started to negotiate contents of possible Chemical Leasing contracts with suitable business partners. The project further aimed at disseminating information on Chemical Leasing. It successfully attracted globally operating companies in the chemicals sector to explore possibilities to implement Chemical Leasing business models in Mexico. At the international level, the results of the UNIDO project were presented on 20TH September 2005 during a side event of the Strategic Approach to International Chemicals Management (SAICM) Preparation Conference in Vienna. Recommendations and Outlook. To facilitate the promotion and application of Chemical Leasing project at international level, UNIDO is currently developing a number of tools to standardize Chemical Leasing projects. These include, among others, Chemical leasing contract models; Chemical Leasing data base to find partners for chemical leasing; and guidelines to implement Chemical Leasing projects and work programmes.     

Determination of Levoglucosan in Atmospheric Fine Particulate Matter

Abstract

A microanalytical method suitable for the quantitative determination of the sugar anhydride levoglucosan in low-volume samples of atmospheric fine particulate matter (PM) has been developed and validated. The method incorporates two sugar anhydrides as quality control standards. The recovery standard sedoheptulosan (2,7-anhydro-β-D-altro-heptulopyranose) in 20 μL solvent is added onto samples of the atmospheric fine PM and aged for 1 hr before ultrasonic extraction with ethylacetate/ triethylamine. The extract is reduced in volume, an internal standard is added (1,5-anhydro-D-mannitol), and a portion of the extract is derivatized with 10% by volume N-trimethylsilylimidazole. The derivatized extract is analyzed by gas chromatography/mass spectrometry (GC/MS). The recovery of levoglucosan using this procedure was 69 ± 6% from five filters amended with 2 μg levoglu-cosan, and the reproducibility of the assay is 9%. The limit of detection is ～0.1 μg/mL, which is equivalent to ～3.5 ng/m³ for a 10 L/min sampler or ～8.7 ng/m³ for a 4 L/min personal sampler (assuming 24-hr integrated samples). We demonstrated that levoglucosan concentrations in collocated samples (expressed as ng/m³) were identical irrespective of whether samples were collected by PM with aerodynamic diameter ≤2.5 μm or PM with aerodynamic diameter ≤10 μm impactors. It was also demonstrated that X-ray fluorescence analysis of samples of atmospheric PM, before levoglucosan determinations, did not alter the levels of levoglucosan.     

Spatial Differences in Outdoor PM10 Mass and Aerosol Composition in Mexico City

Abstract

Twenty-five MiniVol samplers were operated throughout the Mexico City metropolitan region from February 22 through March 22, 1997, to evaluate the variability of PM₁₀ concentrations and composition. The highest PM₁₀ concentrations were found in neighborhoods with unpaved or dirty roads, and elements related to crustal material were the main cause of differences from nearby (<200 m) monitors that were not adjacent to the roadbed. SO₄ ^2?concentrations were homogeneous across the city. SO₄ ^2?measured at the city boundaries was about two-thirds of the concentrations measured within the urbanized area, indicating that most SO₄ ^2? is of regional origin. Elemental carbon (EC) and organic carbon (OC) concentrations were highly variable, with higher concentrations in areas that had high diesel traffic and older vehicles. Spatial correlations among PM₁₀ concentrations were high, even though absolute concentrations were variable, indicating a common effect of meteorology on the concentration or dispersion of local emissions.     

Trace Gases and Particulate Matter Emissions from Wildfires and Agricultural Burning in Northeastern Mexico during the 2000 Fire Season

Abstract

An inventory of air pollutants emitted from forest and agricultural fires in Northeastern Mexico for the period of January to August of 2000 is presented. The emissions estimates were calculated using an emissions factor methodology. The inventory accounts for the emission of carbon monoxide (CO), methane, nonmethane hydrocarbons, ammonia, nitrogen oxides, and particulate matter (PM). Particulate matter emissions include estimates for fine PM and coarse PM. A total of 2479 wildfires were identified in the domain for the period of interest, which represented ~810,000 acres burned and 621,130 short tons emitted (81% being CO). The main source of information used to locate and estimate the extent of the fires came from satellite imagery. A geographic information system was used to determine the type of vegetation burned by each fire. More than 54% of the total area burned during the period of study was land on the State of Tamaulipas. However, >58% of the estimated emissions came from the State of Coahuila. This was because of the mix of vegetation types burned in each state. With respect to the temporal distribution, 76.9% of the fires occurred during the months of April and May consuming almost 78% of the total area burned during the period of study. Analysis of wind forward trajectories of air masses passing through the burned areas and 850-mb wind reanalyses indicate possible transboundary transport of the emissions from Mexico to the United States during the occurrence of the major wildfires identified.     

Theoretical Limits of Errors Due to Anisokinetic Sampling of Particulate Matter

Theoretical estimates of errors in calculated concentrations of particulate matter, sampled with aspirated nozzles under conditions of anisokinetic flow, were based on computed trajectories of particles in fluid streams. In the trajectory determinations gravitational effects on the particles were neglected and the fluid flow patterns approximated by those of a frictionless ideal fluid. The equations of motion were derived considering inertia as the predominant mechanism in the collection of the particulate matter by an aspirated nozzle. The particles were assumed to be spherical in shape, monodisperse, and experiencing drag force as in a real fluid. The equations of motion were solved by a procedure combining an analog and a digital computer. The theoretical error estimates for anisokinetic sampling were compared with experimental data available on investigations with spherical test dust.     

Chemical Mass Balance Model with Fractionation for Apportioning PM2.5: A Test Case for Los Angeles Traffic Sources

Abstract

Chemical mass balance receptor models (CMBs) use measured pollutant concentrations, along with source information, to apportion the contributions of primary sources to the measured concentrations. CMBs can be used to evaluate the accuracy of the emission inventories that underlie State Implementation Plan (SIP) modeling, by providing an allocation of emissions to individual source categories. CMBs, however, traditionally have not accounted for the chemical reaction and differential deposition or fractionation that occur between the source and receptor. This means that they have historically had severe limitations in apportioning secondary particulate matter (PM), which is an especially important component of fine PM (PM_2.5). Stafford and Liljestrand developed a method to account for fractionation in CMBs using depletion factors based on a solution of the steady-state advection-dispersion equation, including gravitational settling, dry deposition, and first-order chemical reaction. In the research presented here, the method of Stafford and Liljestrand was tested using gaseous and PM ambient concentration data from the Los Angeles, CA, air shed, along with traffic source profiles specific to Los Angeles and the CMB7 receptor model of the U.S. Environment Protection Agency. Including fractionation increased nitrate apportioned from 5% and 6% to 83% and 86% for Claremont, CA, and Long Beach, CA, respectively. This is significant, because CMBs have historically had difficulty apportioning nitrate. Including fractionation increased the ammonium apportioned by a factor of 7. The method could be used in future case studies to apportion secondary organic carbon as well.